This repo is official implementation of High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition(CVPR 2023).
conda env create -f environment.yml
We use subdivided MANO to register 3D hand Mesh from "DeepHandMesh". Download joint annotation and our processed dataset from here.
After downloading, put the contents in $root/data
directory.
Download images for DeephandMesh and following the unzip instructions. Then, put the images
folder under $root/data/DeepHandMesh
directory
Download subdivided MANO from here and put the contents under $root/assets/
.
Download MANO from here. Put models
folder under $root/assets/mano
.
Download pretrained model from here and put the contents under $root/model
.
python main.py --test --nmp --nrd
python main.py --nmp --nrd
@InProceedings{Luan_2023_CVPR,
author = {Luan, Tianyu and Zhai, Yuanhao and Meng, Jingjing and Li, Zhong and Chen, Zhang and Xu, Yi and Yuan, Junsong},
title = {High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {16795-16804}
}
This repo inherited code from DeepHandMesh and S2HAND.